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Abstract IA29: Models of postsurgical early and late stage metastasis for improving preclinical adjuvant and metastatic therapy investigations

2013· article· en· W2040905618 on OpenAlexaff
Robert S. Kerbel

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsSunnybrook Hospital
Fundersnot available
KeywordsMedicineCancerPrimary tumorMetastatic breast cancerMetastasisMelanomaOncologyIn vivoBreast cancerDiseaseClinical trialAdjuvant therapyPathologyInternal medicineCancer research

Abstract

fetched live from OpenAlex

Abstract A long standing problem in anti-cancer drug development has been the limited value of preclinical mouse tumor models to reliably predict subsequent clinical activity. All too often highly encouraging preclinical results in mice are followed by complete failure in clinical trials, especially at the randomized phase III level. There are many possible reasons that have been postulated for this preclinical/clinical discrepancy. One which we have been studying for the past decade is the failure to use mouse models which duplicate the challenging circumstance of treating advanced (established) visceral metastatic disease after primary tumors have been surgically resected. Instead, preclinical treatment of established primary tumors or low volume (micro)metastatic disease, often confined to the lungs, have been the historical preclinical model norms. To address this problem we have developed several models of postsurgical advanced metastatic disease involving human tumor xenografts grown in SCID mice, including breast, colorectal or kidney cancer, and melanoma (1). This approach has been extended more recently for postsurgical adjuvant therapy of early stage microscopic metastatic disease (2,3). The established cell lines used for in vivo studies are variants previously selected in vivo for more aggressive spontaneous metastatic capability, which then are sometimes stably tagged with luciferase to permit whole body bioluminescent imaging. Using these models to evaluate the impact of several anti-cancer treatments, consisting mostly of antiangiogenic drugs and/or chemotherapy, either standard maximum tolerated dose or low-dose ‘metronomic’, has highlighted the critical contribution of the extent of metastatic disease to differential therapeutic outcomes, and the prospect of better correlation with clinical outcomes. For example, primary orthotopic tumors, e.g. breast cancer in the mammary fat pad, respond well to treatment with an antiangiogenic drug such as sunitinib, pazopanib or anti-VEGFR-2 antibodies whereas mice with advanced metastases in sites such as the liver or lungs do not, e.g. no prolongation of survival is observed (4). Adding chemotherapy, e.g. paclitaxel to sunitinib did not change the results, whereas adding DC101, an anti-VEGFR-2 antibody, to the same chemotherapy regimen did result in a modest survival improvement (thus mimicking the metastatic breast cancer E2100 phase III results of bevacizumab plus paclitaxel chemotherapy) (4). The observed lack of sunitinib efficacy alone or with chemotherapy when treating mice with advanced metastases mimics three failed phase III clinical trial results of this drug with or without chemotherapy in metastatic breast cancer patients (5). In addition, we have noted that successful treatment of mice with advanced systemic metastatic breast, melanoma or renal cell cancer, e.g. with low-dose metronomic chemotherapy plus an antiangiogenic drug such that overall survival is meaningfully prolonged, sometimes results in the emergence of overt spontaneous brain metastases(1,6,7). Thus, in mice, the brain appears to be a protective sanctuary for the survival and progressive growth of microscopic into macroscopic metastases, as already well known in the clinic. More recent studies have indicated how the brain microenvironment can contribute to the development of melanoma metastases in this organ environment e.g. the interaction of endothelins (ETs) with (elevated) endothelin receptor B expression by the brain melanoma metastatic variants (8). In summary, models of postsurgical advanced metastatic disease to undertake experimental therapeutic studies appear to have a greater degree of clinical relevance compared to most conventional primary tumor therapy models. We are now extending this approach to the development of postsurgical models of early stage microscopic metastatic disease to mimic adjuvant therapy in the clinic (2,9,10); some of our previous (2009) results indicated that adjuvant antiangiogenic therapy may actually worsen eventual survival outcomes of mice with early stage disease (2), a finding for which there is now some preliminary clinical support based on a recent phase III clinical trial assessing treatment of postsurgical early stage colorectal cancer patients with bevacizumab plus chemotherapy (11,12). References: 1. Francia G, Cruz-Munoz W, Man S, Xu P, Kerbel RS. Perspective: Mouse models of advanced spontaneous metastasis for experimental therapeutics. Nature Reviews Cancer 2011; 11:135-41. 2. Ebos JML, Lee CR, Cruz-Munoz W, Bjarnason GA, Christensen JG, Kerbel RS. Accelerated metastasis after short-term treatment with a potent inhibitor of tumor angiogenesis. Cancer Cell 2009; 15:232-9. 3. Ebos JML and Kerbel RS. Impact of antiangiogenic therapy on invasion, disease progression, and metastasis. Nat Rev Clin Oncol 2011; 8:210-21. 4. Guerin E, Man S, Xu P, Kerbel RS. Preclinical recapitulation of antiangiogenic drug clinical efficacy in breast cancer using mice with postsurgical advanced metastatic disease. Submitted for publication. 5. Kerbel RS. Strategies for improving the clinical benefit of antiangiogenic drug based therapies for breast cancer. J Mammary Gland Biol Neoplasia 2012; in press. 6. Francia G, Man S, Lee C-J, et al. Comparative impact of trastuzumab and cyclophosphamide on HER-2 positive human breast cancer xenografts. Clin Cancer Res 2009; 15:6358-66. 7. Cruz-Munoz W, Man S, Xu P, Kerbel RS. Development of a preclinical model of spontaneous human melanoma CNS metastasis. Cancer Res 2008; 68:4500-5. 8. Cruz-Munoz W, Jaramillo ML, Man S, et al. Roles for Endothelin Receptor B and BCL2A1 in Spontaneous CNS Metastasis of Melanoma. Cancer Res 2012; 72:4909-19. 9. Hackl C, Man S, Francia G, Xu P, Kerbel RS. Metronomic oral topotecan prolongs survival and reduces liver metastasis in improved preclinical orthotopic and adjuvant therapy colon cancer models. Gut 2012; epub ahead of print. 10. Wang D, Margalit O, DuBois RN. Metronomic topotecan for colorectal cancer: a promising new option. Gut 2012; epub ahead of print. 11. de GA, Van CE, Schmoll HJ, et al. Bevacizumab plus oxaliplatin-based chemotherapy as adjuvant treatment for colon cancer (AVANT): a phase 3 randomised controlled trial. Lancet Oncol 2012; 13:1225-33. 12. Seymour MT. Adjuvant bevacizumab in colon cancer: where did we go wrong? Lancet Oncol 2012; 13:1176-7. Citation Format: Robert S. Kerbel. Models of postsurgical early and late stage metastasis for improving preclinical adjuvant and metastatic therapy investigations. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Invasion and Metastasis; Jan 20-23, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;73(3 Suppl):Abstract nr IA29.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.166
GPT teacher head0.442
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2013
Admission routes1
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